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Weighted Sum Rate Enhancement by Using Dual-Side IOS-Assisted Full-Duplex for Multi-User MIMO Systems

Sisai Fang, Gaojie Chen, Chong Huang, Yue Gao, Yonghui Li, Kai-Kit Wong, Jonathon A. Chambers

TL;DR

This work introduces a dual-side IOS–assisted full-duplex MIMO system for multi-user networks and targets maximizing the weighted sum rate across downlink and uplink transmissions. It adopts a WMMSE reformulation with alternating optimization, using a Lagrangian dual approach for beamforming and a QCQP solution for simultaneous reflection/refraction phase shifts on both IOS faces. Numerical results show substantial WSR gains of the dual-side IOS over traditional single-side IOS and no IOS configurations, and demonstrate convergence and robustness to phase-quantization. The findings highlight dual-sided metasurfaces as a viable design path to boost spectral efficiency and SI mitigation in next-generation IoT/6G networks.

Abstract

This paper established a novel multi-input multi-output (MIMO) communication network, in the presence of full-duplex (FD) transmitters and receivers with the assistance of dual-side intelligent omni surface. Compared with the traditional IOS, the dual-side IOS allows signals from both sides to reflect and refract simultaneously, which further exploits the potential of metasurfaces to avoid frequency dependence, and size, weight, and power (SWaP) limitations. By considering both the downlink and uplink transmissions, we aim to maximize the weighted sum rate, subject to the transmit power constraints of the transmitter and the users and the dual-side reflecting and refracting phase shifts constraints. However, the formulated sum rate maximization problem is not convex, hence we exploit the weighted minimum mean square error (WMMSE) approach, and tackle the original problem iteratively by solving two sub-problems. For the beamforming matrices optimizations of the downlink and uplink, we resort to the Lagrangian dual method combined with a bisection search to obtain the results. Furthermore, we resort to the quadratically constrained quadratic programming (QCQP) method to optimize the reflecting and refracting phase shifts of both sides of the IOS. In addition, we introduce the case without a dual-side IOS for comparison. Simulation results validate the efficacy of the proposed algorithm and demonstrate the superiority of the dual-side IOS.

Weighted Sum Rate Enhancement by Using Dual-Side IOS-Assisted Full-Duplex for Multi-User MIMO Systems

TL;DR

This work introduces a dual-side IOS–assisted full-duplex MIMO system for multi-user networks and targets maximizing the weighted sum rate across downlink and uplink transmissions. It adopts a WMMSE reformulation with alternating optimization, using a Lagrangian dual approach for beamforming and a QCQP solution for simultaneous reflection/refraction phase shifts on both IOS faces. Numerical results show substantial WSR gains of the dual-side IOS over traditional single-side IOS and no IOS configurations, and demonstrate convergence and robustness to phase-quantization. The findings highlight dual-sided metasurfaces as a viable design path to boost spectral efficiency and SI mitigation in next-generation IoT/6G networks.

Abstract

This paper established a novel multi-input multi-output (MIMO) communication network, in the presence of full-duplex (FD) transmitters and receivers with the assistance of dual-side intelligent omni surface. Compared with the traditional IOS, the dual-side IOS allows signals from both sides to reflect and refract simultaneously, which further exploits the potential of metasurfaces to avoid frequency dependence, and size, weight, and power (SWaP) limitations. By considering both the downlink and uplink transmissions, we aim to maximize the weighted sum rate, subject to the transmit power constraints of the transmitter and the users and the dual-side reflecting and refracting phase shifts constraints. However, the formulated sum rate maximization problem is not convex, hence we exploit the weighted minimum mean square error (WMMSE) approach, and tackle the original problem iteratively by solving two sub-problems. For the beamforming matrices optimizations of the downlink and uplink, we resort to the Lagrangian dual method combined with a bisection search to obtain the results. Furthermore, we resort to the quadratically constrained quadratic programming (QCQP) method to optimize the reflecting and refracting phase shifts of both sides of the IOS. In addition, we introduce the case without a dual-side IOS for comparison. Simulation results validate the efficacy of the proposed algorithm and demonstrate the superiority of the dual-side IOS.
Paper Structure (13 sections, 68 equations, 6 figures, 2 algorithms)

This paper contains 13 sections, 68 equations, 6 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System model
  4. Problem formulation
  5. Optimization for the Weighted Sum Rate Enhancement
  6. Problem Reformulation
  7. Optimizing the beamforming matrices at the transmitter and users
  8. Optimizing the reflecting and refracting phase shift matrices of the dual-side IOS
  9. Overall algorithm and complexity analysis
  10. Numerical Results
  11. Conclusion
  12. Derivations of \ref{['V_kd']} and \ref{['V_ku']}
  13. Derivations of \ref{['g_theta_phi']}

Figures (6)

  • Figure 1: An illustration of a dual-side IOS-assisted FD multi-user MIMO system.
  • Figure 2: Iteration behaviors of the formulated problem for different schemes.
  • Figure 3: Three schemes with different $L$.
  • Figure 4: Three schemes with different downlink transmit power $P_B$.
  • Figure 5: Three schemes with different uplink transmit power $P_U$.
  • ...and 1 more figures